Multifarious colloidal structures: new insight into ternary and quadripartite ordered assemblies.

DNA-mediated assembly of colloidal particles can be utilized to produce a variety of structures which may have desirable phononic, photonic, or electronic transport properties. Recent developments in linker-mediated assembly processes allow for interactions to be coordinated between many different types of colloidal particles more easily and with fewer unique sequences than direct hybridization. However, the dynamics of colloidal self-assembly becomes increasingly more complex when coordinating interactions between three or more distinct interacting elements. In such cases particle pairs with similar binding energies are allowed to interact unpredictably, and enthalpically degenerate binding sites will be noticeably more present while numerous secondary phases may also result from the self-assembly process. Therefore, it is necessary to develop procedures for predicting feasible superstructure geometries for these systems before they can be implemented in material design. Here we investigate the formation of multifarious ordered structures through self-assembly of multiple types of spherically symmetrical colloidal particles with a variety of interaction matrices. We utilize Molecular Dynamics (MD) simulations to study the growth behavior of systems with different types of interacting elements and different particle sizes, and also predict the formation and stability of the target structures. We also study the phononic spectra of various ternary structures in order to identify the influence of key structural parameters on phonon bandgap frequencies and ranges. Our results provide direct guidelines for designing ternary and quadripartite multifarious colloidal structures, and motivate new directions for future experimental work to target formation of multi-component colloidal superstructures beyond the well-established binary symmetries studied in the past.

Investigation of Geometric Landscape and Structure-Property Relations for Colloidal Superstructures Using Genetic Algorithm.

Over the past two decades, colloidal particles with a variety of shapes, sizes, and compositions have been synthesized and characterized successfully. One of the most important applications for colloidal building blocks is to engineer functional structures as mechanical, electrical, and optical metamaterials. However, complex interaction dynamics between the building blocks as well as sophisticated structure-property relationships make it challenging to design structures with predictable target properties. In this paper, we implement an inverse material design framework using Genetic Algorithm (GA)-based techniques to streamline the design of colloidal structures based on target properties. We investigate spherical particles as well as colloidal molecules of different sizes and shapes and evaluate a Geometric Landscape Accessibility parameter that identifies the size of feasible domains within the geometric phase space of each structure. Considering target photonic properties, our GA-assisted framework is further utilized to identify sets of building blocks and structures that lead to various target values for the size of the photonic band gaps. The proposed framework in this study will provide new insight for predictive computational material design approaches and help establish more efficient ways of understanding structure-property relations in sub-micrometer-scale materials.

Self-assembly with colloidal clusters: facile crystal design using connectivity landscape analysis.

Recent experimental and theoretical studies demonstrate that prefabricated micron-scale colloidal clusters functionalized with DNA oligomers offer a practical way for introducing anisotropic interactions, significantly extending the scope of DNA-mediated colloidal assembly, and enabling the formation of interesting crystalline superstructures that are otherwise inaccessible with short-ranged, spherically symmetric interactions. However, it is apparent that the high-dimensional parameter space that defines the geometric and interaction properties of such systems poses an obstacle to assembly design and optimization. Here, we present a geometrical analysis that generates connectivity landscapes for target superstructures, greatly reducing the space over which subsequent experimental trials must search. We focus on several superstructures that are assembled from binary systems comprised of 'merged' or 'sintered' tetrahedral clusters and single spheres. We also validate and extend the analytical constraint approach with direct MD simulations of superstructure nucleation and growth.

Colloidal Cluster Assembly into Ordered Superstructures via Engineered Directional Binding.

Recent experimental studies have demonstrated a facile route for fabricating large numbers of geometrically uniform colloidal clusters out of submicron DNA-functionalized spheres. These clusters are ideally suited for use as anisotropic building blocks for hierarchical assembly of superstructures with symmetries that are otherwise inaccessible with simple spherical particles. We study computationally the self-assembly of cubic, tetrahedral, and octahedral clusters mediated by "bond spheres" that dock with the clusters at specific preferential sites, providing robust and well-defined directional bonding. We analyze the assembly process with a combination of direct molecular dynamics simulations of superstructure growth and state-of-the-art umbrella sampling techniques to compute nucleation free energy profiles. The simulations confirm the versatility and robustness of hierarchical cluster assembly but also reveal potential obstacles in the form of energetically accessible defect states. We find and study solutions for bypassing these defects that rely on appropriate selection of particle size and interparticle interaction as a function of building block shape and, therefore, provide operational guidelines for future experimental demonstrations.

Up and down translocation events and electric double-layer formation inside solid-state nanopores.

We present a theoretical study of nanorod translocation events through solid-state nanopores of different sizes which result in positive or negative ion conductance changes. Using theoretical models, we show that positive conductance changes or up events happen for nanopore diameters smaller than a transition diameter dt, and negative conductance changes or down events occur for nanopore diameters larger than dt. We investigate the underlying physics of such translocation phenomena and describe the significance of the electric double-layer effects for nanopores with small diameters. Furthermore, for nanopores with large diameters, it is shown that a geometric model, formulated based on the nanoparticle blockade inside the nanopore, provides a straightforward and reasonably accurate prediction of ion conductance change. Based on this concept, we also implement a method to distinguish and detect nanorods of different sizes by focusing solely on the sign and not the exact value of the conductance change.

NEMS With Broken T Symmetry: Graphene Based Unidirectional Acoustic Transmission Lines.

In this work we discuss the idea of one-way acoustic signal isolation in low dimensional nanoelectromechanical oscillators. We report a theoretical study showing that one-way conversion between in-phase and anti-phase vibrational modes of a double layer graphene nanoribbon is achieved by introducing spatio-temporal modulation of system properties. The required modulation length in order to reach full conversion between the two modes is subsequently calculated. Generalization of the method beyond graphene nanoribbons and realization of a NEMS signal isolator are also discussed.

Gold nanorod translocations and charge measurement through solid-state nanopores.

We study translocations of gold nanoparticles and nanorods through silicon nitride nanopores and present a method for determining the surface charge of nanorods from the magnitude of the ionic current change as nanorods pass through the pore. Positively charged nanorods and spherical nanoparticles with average diameters 10 nm and average nanorod lengths between 44 and 65 nm were translocated through 40 nm thick nanopores with diameters between 19 and 27 nm in 1, 10, or 100 mM KCl solutions. Nanorod passage through the nanopores decreases ion current in larger diameter pores, as in the case of typical Coulter counters, but it increases ion current in smaller diameter nanopores, likely because of the interaction of the nanopore's and nanoparticle's double layers. The presented method predicts a surface charge of 26 mC/m(2) for 44 nm long gold nanorods and 18 mC/m(2) for 65 nm long gold nanorods and facilitates future studies of ligand coverage and surface charge effects in anisotropic particles.

Strain- and defect-mediated thermal conductivity in silicon nanowires.

The unique thermal transport of insulating nanostructures is attributed to the convergence of material length scales with the mean free paths of quantized lattice vibrations known as phonons, enabling promising next-generation thermal transistors, thermal barriers, and thermoelectrics. Apart from size, strain and defects are also known to drastically affect heat transport when introduced in an otherwise undisturbed crystalline lattice. Here we report the first experimental measurements of the effect of both spatially uniform strain and point defects on thermal conductivity of an individual suspended nanowire using in situ Raman piezothermography. Our results show that whereas phononic transport in undoped Si nanowires with diameters in the range of 170-180 nm is largely unaffected by uniform elastic tensile strain, another means of disturbing a pristine lattice, namely, point defects introduced via ion bombardment, can reduce the thermal conductivity by over 70%. In addition to discerning surface- and core-governed pathways for controlling thermal transport in phonon-dominated insulators and semiconductors, we expect our novel approach to have broad applicability to a wide class of functional one- and two-dimensional nanomaterials.

Size dependent elastic moduli of CdSe nanocrystal superlattices predicted from atomistic and coarse grained models.

Nanocrystal superlattices are materials formed by assembly of monodisperse nanocrystal building blocks that are tunable in composition, size, shape, and surface functionalization. Such materials offer the potential to realize unprecedented combinations of physical properties, but theoretical prediction of such properties, particularly elastic properties, remains a challenge. Here we report the Young's moduli, bulk moduli, and Poisson's ratios of CdSe nanocrystal superlattices computed from fully atomistic molecular dynamics simulations, coarse grained models, and effective medium theory. The atomistic simulations yield Young's moduli in the 4-5 GPa range, in agreement with previously reported results for similar nanocrystal superlattice systems. A clear increase of Young's modulus and bulk modulus with increasing nanocrystal core size is observed, while Poisson's ratio decreases slightly with core size. Effective medium theory overpredicts the moduli, and it is surmised that this arises from its neglect of the atomic-level details of the of the core-ligand interface. The coarse grained calculations, using existing nanocrystal interaction models from the literature, also show similar increases with core size but predict moduli that are two orders of magnitude lower than the present atomistic results and previous literature. It is concluded that coarse grained models, in their current form, are not appropriate for calculating elastic properties of nanocrystal superlattices and that fully atomistic models are better suited for this purpose.